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A new €3.5m research project, which aims to improve the performance of modern parallel computing technology, is expected to have substantial implications for the future of the renewables industry.

Research findings from the European Commission-funded ParaPhrase Project could provide solutions which can be applied in the analysis and processing of massive environmental data gathered from sensors across a network of devices for renewable energy production — including wind turbines, photovoltaic and thermal solar panels — ultimately influencing their yield and performance.

Supported by the Seventh Framework Programme (FP7) for Research and Technological Development — the EU’s main instrument for funding research — it will bring together expertise from academic institutions and industry specialists across five countries, including Robert Gordon University’s (RGU) Institute for Innovation Design and Sustainability Research (IDEAS) in Aberdeen and St Andrews University, who will co-ordinate the project.

Starting this month and set to run for three years, the project at RGU — which has been awarded €638,000 to undertake research activities — will involve academics, researchers and PhD students of parallel computing and computational science at the School of Computing and IDEAS Research Institute. The project will look to exploit high performance computers effectively to support modern demands for computing power in the home and industry, maximising the speed of processors working together ‘in parallel’ to give peak performance.

Improved forecasting

Dr Horacio González-Vélez, a lecturer at the School of Computing and the Principal Investigator of the project at RGU, said: “By applying advanced parallel processing techniques, the weather sensors currently mounted on power plants and the amount of data this produces could be augmented, with additional measure points and enhanced analysis to further improve models and forecasts.

“These improved weather predictions could in turn be utilised to more precisely predict the energy production at a certain point in time. If these predictions were then used in a Smart-grid scenario for example, they could help calculate the energy needed from distinct power resources faster and more accurately.”

In all, the project involves six academic institutions including St Andrews University, Robert Gordon University, the University of Stuttgart in Germany, Queens’ University Belfast, and the Universities of Torino and Pisa in Italy. Experts from industrial partners include Erlang Solutions in the UK, Mellanox in Israel and the Software Competence Centre in Austria.

For more information on the project visit

04 October 2011